Knowledge that Transforms

IPOs with underwriters that retain an elite law firm exhibit a lower average first-day return. This empirical pattern remains after controlling for an extensive set of proxies associated with existing explanations of IPO initial returns. We rationalize this finding with a pre-IPO pricing model, in which underwriters convey their lack of conflicts of interest to the issuer by engaging an elite law firm. Consistent with this selection channel and our model’s predictions, we find a lower incidence of elite law firm involvement and a larger difference in average first-day return associated with elite law firms during the dot-com period. We document similar findings with respect to the dispersion of IPO first-day returns and a pattern in the issuers’ re-hiring decision of investment banks consistent with our theory.

We examine the relationships between ownership structure and both earnings and risk-taking among community banks before, during, and after the US financial crisis. We find that publicly-held small community banks had lower earnings than privately-held ones before the recession, but had higher earnings during and after the recession. Publicly-held small community banks exhibited similar risk-taking to privately-held ones before and during the recession, but greater risk-taking after. We also find that publicly-held small community banks de-risked more slowly than privately-held ones following the recession. Large community banks, on the other hand, show no consistent relationship between ownership structure and earnings, and a strong cyclical relationship between ownership structure and risk-taking. These findings expand our understanding of how community bank performance and capital accumulation behaves through different cyclical periods, and how ownership structure affects that behavior.

A frequent problem in binary classification is class imbalance between a minority and a majority class such as defaults and non-defaults in default prediction. In this article, we introduce a novel binary classification model, the Grabit model, which is obtained by applying gradient tree boosting to the Tobit model. We show how this model can leverage auxiliary data to obtain increased predictive accuracy for imbalanced data. We apply the Grabit model to predicting defaults on loans made to Swiss small and medium-sized enterprises (SME) and obtain a large and significant improvement in predictive performance compared to other state-of-the-art approaches.

This paper studies cross-sectional determinants of the exposure of U.K. firms to Brexit, an event which resulted in an unprecedented rise in political uncertainty. We find that internationalization has a moderating effect on Brexit exposure which goes beyond the pure currency translation effect and is consistent with international activities acting as a diversification mechanism for domestic risks. We also provide some indicative evidence that high-growth firms are more affected by Brexit. At the industry level, we show that Financials and firms in the consumer-facing sectors have the highest exposure to Brexit-related uncertainty. Knowledge of the variation in exposure of individual firms and sectors to political uncertainty associated with major political events can assist managers, investors and policymakers in taking remedial actions to limit its impact.

We examine how the issuer-paid incumbent credit rating agencies (CRAs) in China adjust their rating strategies in response to the 2010 entry of an independent credit rating agency, China Bond Rating (CBR) between 2006 and 2015. The business model that CBR employs is a combination of the public utility model and the investor-paid model. We find that the CBR's ratings coverage effectively reduced the information asymmetry in the Chinese corporate bond market. The evidence shows decreased ratings inflation and increased informativeness of rating change announcements by incumbent issuer-paid CRAs after CBR entered the market. The findings suggest that a firm's credibility is an important channel driving issuer-paid incumbent CRAs’ strategic ratings. Our paper provides new information and insight into the debate of whether CRAs with alternative business models can alleviate the information asymmetry problem.

We provide empirical evidence of the post-investment performance and survivorship profile of angel-backed companies, filling a long-standing gap within the entrepreneurial finance literature. Using a unique database of 111 angel-backed companies that received angel investments between 2008 and 2012 and at least 3 years of post-investment financial data, we develop an innovative performance metric and show that the performance and the probability of survival of investee companies are positively affected by the presence of angel syndicates and the hands-on involvement of business angels, while they are negatively related to the intensity of angel monitoring and the time structure of equity provision. Our results are robust to several endogeneity tests and provide insights on the multifaceted contributions of angel investors to the performance and survival of new ventures.

I use account-level credit card and term loan data to analyze consumers’ responses to anticipated increases in cash on hand following term loan run-offs. Financial constraints are elicited using past credit card payment behavior and can explain the response of credit card but not term loan expenditure: unconstrained consumers are 23% more likely to finance new durable goods with term loans after the run-off. The results provide evidence of consumers engaging in sequential term loan borrowing.

We propose a generic framework for performance attribution in monetary terms. Through a second-order Taylor approximation, the changes in portfolio value are attributed to a set of systematic risk factors. By considering two error terms arising from the Taylor approximation, combined with an exact definition of the carry term, we derive a residual-free performance attribution framework, where we exert control over the size of the error terms. The framework incorporates foreign exchange rates and transaction costs, which is illustrated by simulating a European investor acting on the U.S. fixed income market. For the out-of-sample period, we show that we can attribute almost all portfolio value differences and variance using six risk factors obtained from principal component analysis. The results show that our method, in combination with high-quality estimates of risk factors, outperforms other fixed-income attribution models from the literature.

We consider market players with tail-risk-seeking behaviour modelled by S-shaped utility, as introduced by Kahneman and Tversky. We argue that risk measures such as value at risk (VaR) and expected shortfall (ES) are ineffective in constraining such players, as such measures cannot reduce the traders expected S-shaped utilities. Indeed, when designing payoffs aiming to maximize utility under a VaR or ES risk limit, the players will attain the same supremum of expected utility with or without VaR or ES limits. By contrast, we show that risk management constraints based on a second more conventional concave utility function can reduce the maximum S-shaped utility that can be achieved by the investor. Indeed, product designs leading to progressively larger S-shaped utilities will lead to progressively lower expected constraining conventional utilities, violating the related risk limit. These results hold in a variety of market models, including the Black Scholes options model, and are particularly relevant for risk managers given the historical role of VaR and the endorsement of ES by the Basel committee in 2012–2013.

We explore the impact of capital adequacy requirements on financial institutions’ risk-taking behavior from a novel perspective. Specifically, we show that an important feature of the risk-based capital (RBC) system—a built-in diversification benefit in aggregating risk categories—induces moral hazard. We find that insurers that face lower marginal RBC costs of fixed-income (FI) investment tend to purchase riskier FI securities. This relationship holds even when lower marginal RBC costs result from increased risk in other risk categories, which is an unintended consequence of the RBC's square root rule. Using Hurricanes Katrina and Sandy as exogenous shocks to the RBC cost, we find that insurers that suffered more in the two disasters undertook more risk in their FI investments and witnessed an increase in their overall risk. We further show that insurers with a high RBC cost sell similar risky bonds during the financial crisis, presenting a source of systemic risk. These results provide an important regulatory implication for minimum capital calculation in capital regulation regimes.